Final answer:
The correct equation for the line of best fit between hours studied and exam grade cannot be determined without the specific data set. Statistical analysis such as least squares regression is used to find the line that most closely represents the data.
Step-by-step explanation:
Finding the Equation for the Line of Best Fit
The question asks whether it pays to study for an exam by looking for a linear relationship between the number of hours studied (x) and the exam grade received (y). To find the equation for the line of best fit, we seek a linear equation that most accurately represents this relationship. The general form of a linear equation is y = mx + b, where m is the slope and b is the y-intercept.
In this case, the information provided suggests the line of best fit for a specific data set was found to be ŷ = -173.51 + 4.83x. However, for the new data provided or similar exercises, the choices given—A) y = 76.4 + 1.2x, B) y = 82.5 + 0.8x, C) y = 70.2 + 1.5x, and D) y = 78.6 + 1.1x—need to be evaluated based on the data set in the question. As those data points are not provided, we cannot determine the correct new line. Typically, the correct equation should be selected based on statistical analysis such as least squares regression or the median--median line approach.
The slope (m) in a regression line indicates how much the dependent variable (y) is expected to increase when the independent variable (x) increases by one unit. It's critical to note that the equation provided above from the information supplied to the student (ŷ = -173.51 + 4.83x) is an example from an unknown dataset and may not match the choices provided for a different dataset. Without additional context or data, we cannot assert which of the provided equations is the correct line of best fit.